JP2014533581A - Predict, visualize, and control drug delivery with an infusion pump - Google Patents

Abstract

A system for predicting a drug delivery profile as described herein includes at least one drug pump and / or controllable valve that generates a flow of drug. The drug pump and / or controllable valve supplies at least a fixed amount of the first drug. The system includes at least one carrier fluid pump and / or another controllable valve that generates a carrier fluid flow, and a merge structure configured to generate a mixed flow in response to the drug flow and the carrier fluid flow. A fluid path for carrying the mixed flow between the confluence structure and the delivery point. The system further includes a processing device configured to predict a drug delivery profile at the delivery point based on determining an expected time change in drug concentration at the delivery point using at least a mixed flow model. The model includes a plurality of parameters relating to the propagation of the mixed flow through the fluid path.

Description

  The present disclosure relates to a control system for an infusion pump.

BACKGROUND Drug infusion systems used to administer medication to a patient typically include a pump for delivering a volume of medication and another pump for delivering a volume of carrier fluid. The drug and carrier fluid are mixed together at a junction, such as a manifold, and conveyed to the patient via the fluid path. The volume of the fluid pathway is referred to as “dead volume” (sometimes referred to as “dead space”) and constitutes the space that the fluid traverses before the drug can reach the patient. Dead volume can result in considerable discrepancies between the intended delivery profile and the actual delivery profile of the drug delivered to the patient. Such inconsistencies can result in delayed delivery of the intended dose of drug to the patient at the desired time.

SUMMARY The present disclosure features methods and systems for controlling one or more infusion pumps so that the actual delivery profile of one or more drugs can be controlled. A delivery profile as used in this application refers to the rate of drug delivery at a point of delivery over a range of time. The present disclosure also features a controllable valve that can be used independently or in conjunction with one or more infusion pumps to control the delivery profile of one or more agents. The methods and systems described herein are based on algorithms, some of which predictively model the flow of one or more drug and carrier fluids in at least a portion of the fluid path between the pump and the delivery point. Depends on what you do. Predictive models are: radial diffusion (molecules moving towards the pipe or catheter wall), axial diffusion (molecules moving along the flow axis), laminar flow (smooth bulk fluid flow), specific drugs Multiple physical parameters, including their physicochemical properties, and their interactions can be taken into account and can therefore be more accurate than empirical models derived primarily from up-to-date data. The output of the infusion pump and / or controllable valve can be adjusted based on a delivery profile calculated using one or more of the predictive models.

  In one aspect, a system for predicting one or more drug delivery profiles includes at least one drug pump that generates a flow of drug. The drug pump supplies a fixed amount of at least the first drug. The system comprises at least one carrier fluid pump for generating a carrier fluid flow, a merging structure configured to receive a drug flow and a carrier fluid flow to generate a mixed flow, and a merging structure and a delivery point. And a fluid path for carrying the mixed stream therebetween. The system further includes a processing device configured to predict a drug delivery profile at the delivery point based at least on using a model of the mixed flow to determine an expected time change in the concentration of the drug at the delivery point. The model includes a plurality of parameters relating to the propagation of the mixed flow through the fluid path.

  In another aspect, a method for predicting the rate of delivery of a drug at a delivery point includes one or more operations on a processing device for a drug pump that delivers a volume of drug and a carrier fluid pump that delivers a volume of carrier fluid. Including receiving parameters. The method determines a drug delivery rate at the delivery point by predicting a time variation in the concentration of the drug at the delivery point based at least on a mathematical model of the mixed flow through the fluid path terminating at the delivery point by the processing device. Including. The mixed flow includes drug and carrier fluid, and the model includes one or more operating parameters and a plurality of flow parameters related to a mathematical model of the mixed flow.

  In another aspect, a system for controlling a drug delivery profile includes at least one drug pump that generates a flow of drug and at least one carrier fluid pump that generates a flow of carrier fluid. The drug pump supplies a fixed amount of at least the first drug. The system includes a merging structure configured to receive a drug flow and a carrier fluid flow to generate a mixed flow, and a fluid path for carrying the mixed flow between the merging structure and a delivery point. The system further provides drug delivery at the delivery point by controlling the drug flow rate and the carrier fluid flow rate such that the ratio between the drug flow rate and the carrier fluid flow rate is substantially fixed over a range of time. A control module configured to control the profile is included. The mixed flow is varied to achieve a specific drug delivery profile.

  In another aspect, a method for controlling a drug delivery profile includes information about a drug flow rate for a drug pump supplying a fixed amount of drug and a carrier fluid for a carrier fluid pump supplying a fixed amount of carrier fluid in a processing device. Including receiving information about the flow rate. The method includes: at a delivery point by adjusting a drug flow rate and a carrier fluid flow rate so that the ratio of the drug flow rate to the carrier fluid flow rate is substantially fixed over a range of time by a control module. It also includes controlling the drug delivery profile.

  In another aspect, a method for predicting a delivery rate of a drug at a delivery point includes a first container that supplies a fixed amount of drug and a fixed amount of carrier fluid, both at a fixed pressure. Receiving at the processing device one or more operating parameters for the two containers. The pre-defined pressure can be adjusted by a constant force such as a linear pressure control valve or gravity. The method determines a drug delivery rate at the delivery point by predicting a time variation in the concentration of the drug at the delivery point based at least on a mathematical model of the mixed flow through the fluid path terminating at the delivery point by the processing device. Including. The mixed flow includes drug and carrier fluid, and the model includes one or more operating parameters and a plurality of flow parameters related to a mathematical model of the mixed flow.

  In another aspect, a system for controlling a drug delivery profile includes a first controllable valve that generates a flow of drug and a second controllable valve that controls the flow of carrier fluid. The system also includes a merging structure configured to receive a drug flow and a carrier fluid flow to generate a mixed flow, and a fluid path for carrying the mixed flow between the merging structure and a delivery point. The system further provides a delivery point by controlling the resistance to flow the carrier fluid flow under constant pressure such that the ratio between the drug flow and the carrier fluid flow is substantially fixed over a range of time. A control module configured to control the drug delivery profile at The mixed flow is varied to achieve a specific drug delivery profile.

  In another aspect, the computer-readable storage device, when executed, causes the processor to receive one or more operating parameters related to a drug pump that supplies a fixed amount of drug and a carrier fluid pump that supplies a fixed amount of carrier fluid. Is encoded on top of it. The instructions further define a delivery rate of the drug at the delivery point by predicting a time change in the concentration of the drug at the delivery point based at least on a mathematical model of the mixed flow through the fluid path terminating at the delivery point. Let The mixed flow includes drug and carrier fluid, and the model includes one or more operating parameters and a plurality of flow parameters related to a mathematical model of the mixed flow.

  In another aspect, the computer readable storage device, when executed, provides information about the flow rate of the drug with respect to the drug pump that supplies a fixed amount of drug to the processor and the carrier fluid with respect to the carrier fluid pump that supplies the fixed amount of carrier fluid. Encode instructions to receive information about the flow rate on it. The instructions further provide the processor with a delivery point by controlling the drug flow rate and the carrier fluid flow rate so that the ratio between the drug flow rate and the carrier fluid flow rate is substantially fixed over a range of time. Control the drug delivery profile.

  Implementations can include one or more of the following aspects, either individually or in combination. For example, various implementations can include combinations and sub-combinations of two or more of the following features.

  The control module can be configured to control drug flow and carrier fluid flow such that a specific drug delivery profile is achieved at a future time. The control module can be further configured to calculate a drug flow rate and a carrier fluid flow rate at a given time such that a specific drug delivery profile is achieved at a future time. The display device can display data about the predicted drug delivery profile. The at least one alarm is a corresponding predefined desired at least one of i) current drug flow rate, ii) current carrier fluid rate, or iii) predicted drug delivery profile associated with the drug. Or it can be configured to trigger upon detection of being out of the safe range. The safe range associated with the drug can be retrieved from the database. The at least one sensor can be configured to provide data about the flow rate of the mixed stream in a particular portion of the delivery path. The control module can be configured to control drug flow and carrier fluid flow such that the ratio of drug and carrier fluid in the mixed flow over a given portion of the fluid path is substantially fixed. The processing device can be further configured to predict a drug delivery profile at the delivery point based on user input parameters for drug flow and carrier flow.

  Parameters related to the propagation of the mixed flow through the fluid path may include one or more of i) radial diffusion, ii) axial diffusion, iii) laminar flow through the fluid path, or iv) the physical or chemical properties of the drug. Characterizing parameters can be included. In some implementations, the parameters related to the propagation of the mixed flow through the fluid path are i) radial diffusion, ii) axial diffusion, iii) laminar flow through the fluid path, and iv) physical or chemical of the drug. It can consist of a combination of two or more parameters characterizing a property. The model can include structural parameters representing at least one characteristic of a drug pump, a carrier fluid pump, a merging structure, or a fluid pathway. In some implementations, the model can consist of a combination of two or more structural parameters representing the characteristics of the drug pump, carrier fluid pump, confluence structure, and fluid pathway. The structural parameter can include a dead volume associated with the fluid pathway. The dead volume can be determined empirically by examining a series of empirical dead volume candidates and selecting the one that best fits the control curve in the least squares sense. The processing device can be further configured to access a storage device that stores the structural parameters.

  The processing device can be configured to identify at least one of a drug pump, a carrier fluid pump, a merging structure, and a fluid path based on the identifier. The identifier may be a radio frequency identification (RFID) tag or barcode, and the processing device is coupled to the RFID tag reader or barcode reader.

  The at least one additional drug pump can deliver a fixed amount of at least a second drug, and the control module can cause the second drug to achieve a specific delivery profile of the second drug at a future time. It is configurable to control the flow of At least one of the drug pump or the carrier fluid pump can be a syringe pump or an infusion pump. The display device can display data about the predicted drug delivery profiles of the first and second drugs.

  The control module can be further configured to adjust the drug delivery rate at the delivery point within a time range by simultaneously controlling the drug flow rate and the carrier fluid flow rate. The concentration of drug in the drug flow can be substantially fixed over a range of time. The control module is capable of adjusting the drug delivery rate to achieve at least a predicted drug delivery rate calculated using a mixed flow model. The control module can be further configured to adjust the drug delivery profile such that over volume delivery over time is substantially reduced while maintaining target drug delivery within tolerance. The model can include a plurality of parameters relating to the propagation of the mixed flow through the fluid path.

  The control module further sets the initial drug flow rate and the initial carrier fluid flow rate to a substantially high value within a corresponding acceptable range at the beginning of the time range, and the delivery point after a predetermined amount of time has elapsed. Can be configured to reduce drug flow rate and carrier fluid flow rate so that a drug delivery profile can be achieved. The predetermined amount of time is substantially equal to the time it takes for the mixed flow to traverse the fluid path when the drug flow rate and carrier fluid flow rate are set to the initial drug flow rate and the initial carrier fluid flow rate, respectively. It can be. At least one controllable valve can be disposed upstream from the merging structure, and the control module controls the drug delivery profile at the delivery point by controlling the flow through the controllable valve. A constant pressure valve can be disposed upstream from the controllable valve, and the constant pressure valve is configured to maintain a constant pressure upstream of the controllable valve for fluid flowing through the controllable valve.

  The methods and systems described herein provide a number of advantages and advantages, including the following (some of which may only be achieved in some of its various aspects and implementations). In general, controlling one or more drug pumps and carrier fluid pumps in relation to each other using an algorithm based in part on a mathematical model facilitates precise control over changes in drug delivery at the delivery point Become. For example, using the model described herein, predicting when and how the output profile at the drug infusion pump must be changed so that a specific delivery profile is achieved at the delivery point it can. Significantly reduce the delay between the activation of the drug infusion pump and the time when the appropriate amount of drug actually reaches the delivery point, which can facilitate rapid drug delivery, especially in a critical care setting . Precise control over the drug delivery profile and warning system to detect dangerous situations avoid potentially life-threatening drug delivery variability and make the drug infusion pump much more reliable and safe. Furthermore, precise control also allows the ability to minimize the volume of fluid delivered. This is an important consideration when delivering infused medications to patients with impaired organ function. The methods and systems described herein can be used to predict a drug delivery profile at a delivery point and to trigger an alarm if the predicted delivery profile is outside the acceptable or safe range. Can also be used. By using one or more resistance valves whose resistance can be controlled substantially continuously or continuously, the flow can be controlled according to the desired setting under a substantially constant upstream pressure.

  Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Although methods and materials similar or equivalent to those described herein can be used, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

  Other features and advantages of the invention will be apparent from the following detailed description and from the claims.

1 is a schematic block diagram of an example system for controlling fluid delivery. FIG. FIG. 6 is a schematic block diagram of another example of a system for controlling fluid delivery. FIG. 5 is a plot showing the relationship between the inner radius of a tube and the flow through the tube. It is a figure of the example of a merging structure. It is a flowchart of the example of the sequence of the operation | movement for reducing the delay of a medicine delivery start. FIG. 6 is a schematic graph of an example of drug concentration along a fluid path. It is a block diagram of a feedback loop. 6 is a flowchart of an example sequence of operations for controlling a drug delivery profile. 1 is a schematic diagram of a computer system. FIG. 6 is a plot illustrating the reduction in an example of drug delivery onset delay. FIG. 6 is a plot illustrating the reduction in an example of drug delivery onset delay. FIG. 6 is a plot illustrating the reduction in an example of drug delivery onset delay. FIG. 4 is a set of plots illustrating improved control for an example drug delivery profile.

DETAILED DESCRIPTION The invention described herein can be implemented in a number of ways. Some useful implementations are described below. The description of an implementation of the invention is not a description of the invention, but the invention is not limited to the detailed implementation described in this section, but is described in broader terms in the claims.

System Overview FIG. 1A shows a schematic block diagram of an example of a system 100 for controlling delivery of fluid, for example, in an infusion pump system. System 100 includes a plurality of infusion pumps 105a, 105b, and 105c (generally 105) that pump fluid (eg, drug and carrier fluid) to target 130. Fluid from the multiple infusion pumps 105 is mixed with each other at the merging structure 120, transported across the fluid path 123, and delivered to the target 130 at the delivery point 125. The fluid output of the infusion pump 105 is possibly controllable by a computing device 115 that communicates with the interface module 110. Although interface module 110 is shown as a separate unit in FIG. 1A, in some implementations interface module 110 may reside on infusion pump 105 or computing device 150.

  The drug pumped by infusion pump 105 can include any compound or composition that can be administered to the target in liquid form. For example, the medicament may comprise a medicament, nutrient, vitamin, hormone, tracer dies, pharmaceutical compound, chemical, or any other substance delivered to the target for prophylactic, therapeutic or diagnostic reasons. it can. Target 130 may include any organism, such as a human patient, animal, or plant, for example. In some implementations, the target 130 can also include a non-biological article such as a device (eg, a reaction chamber) to which the fluid mixture is delivered in a controlled manner.

  Infusion pump 105 is typically used to introduce a fluid, such as a drug as mentioned above, in a target portion. For example, infusion pump 105 can be used to introduce medication into the patient's circulatory system. In general, infusion pump 105 dispenses a controlled amount of fluid over a period of time. In some implementations, the infusion pump 105 delivers a constant amount of fluid at a continuous flow rate. In some implementations, the infusion pump 105 repeatedly delivers a predetermined amount of fluid repeatedly after a predetermined time interval. For example, infusion pump 105 can be configured to deliver a fixed amount of a given drug of 0.1 ml every hour, every minute, and the like. In some implementations, the infusion pump 105 can be configured to deliver a volume of fluid on demand, for example as directed by a healthcare professional or even a patient. In such cases, the infusion pump 105 can also include an overdose protection system to prevent a certain amount of potentially dangerous quantities from being supplied. For example, infusion pump 105 includes safety features (eg, alarms and early shutdown) that activate when there is a risk of undesirable drug interactions or when an operator sets pump parameters outside specified safety limits. Can be a “smart pump”.

  Infusion pump 105 can operate in a variety of ways. For example, the infusion pump 105 may be a syringe pump in which fluid is held in a syringe reservoir and a movable piston controls a certain amount of fluid supply. In some implementations, the infusion pump 105 may be an elastomeric pump in which fluid is retained in a stretchable balloon-like reservoir and pressure from the balloon's elastic wall supplies a fixed amount of fluid. The infusion pump 105 can also include a peristaltic pump in which a set of rollers press down along the length of the flexible tubing, thereby supplying a certain amount of fluid through the tubing. In some implementations of the pump system, other propulsion mechanisms may be used. The infusion pump 105 can also be a multi-channel pump where fluid is supplied in a fixed amount from multiple reservoirs, possibly at different rates.

  Infusion pump 105 may also include one or more ports that receive control signals that control the fluid output from the infusion pump. For example, infusion pump 105 may include a universal serial bus (USB) port for receiving control signals for an actuator that regulates the pressure that controls the fluid output. In some implementations, infusion pump 105 can feature a wireless receiver (eg, a Bluetooth receiver, an infrared receiver, etc.) for receiving control signals. In some implementations, infusion pump 105 may be WiFi enabled so that the infusion pump can receive control signals over a wireless network, such as a wireless local area network (WLAN). In some implementations, infusion pump 105 may be configured to receive control signals on any combination of wired and wireless networks.

  In some implementations, one of the infusion pumps (eg, infusion pump 105c) provides a constant carrier fluid to be mixed with the drug (supplied in a fixed amount from one or more other infusion pumps) in a combined structure. Deliver and deliver the mixed fluid to the target. In general, the amount of volume from the delivered drug is small, so the carrier fluid constitutes a significant portion of the fluid delivered to the target. Various materials such as polymeric materials can be used as the carrier fluid. Some properties of the carrier fluid are: sufficient drug-loading capacity, water solubility when loaded with drug, suitable molecular or weight range, stable carrier-drug binding in body fluids, biodegradability Non-toxic, and general biocompatibility. In some implementations, it may also be desirable for the carrier fluid to be non-immunogenic. The carrier fluid can carry the drug in a variety of ways. In some implementations, the carrier fluid acts as a substrate, and the drug is transported uniformly through the substrate. In some implementations, the carrier fluid acts as a solvent and the drug is dissolved in the carrier fluid. In some implementations, the agent may also be chemically or magnetically conjugated to a carrier fluid molecule. A variety of polymeric materials can be used as the carrier fluid, such as soluble polymers, biodegradable or bioerodible polymers, and mucoadhesive polymers. A typical carrier fluid commonly used clinically can include 0.9% sodium chloride (normal saline) and 5% aqueous dextrose (D5W). However, other carrier fluids can be used in some implementations.

  FIG. 1A shows more or less numbers even though only two infusion pumps 105a and 105b for delivering a constant amount of drug and only one infusion pump 105c for supplying a constant amount of carrier fluid are shown. An infusion pump is also possible. For example, the system may feature only a single infusion pump for delivering a fixed volume of medication and a single infusion pump for supplying a fixed volume of carrier fluid. In some implementations, a greater number of infusion pumps (eg, 3 or 4 or more) can be used to deliver a fixed amount of multiple drugs. In some implementations, multiple infusion pumps can be used to deliver a quantity of two or more different types of carrier fluids.

  In general, a carrier fluid supplied in a fixed amount from infusion pump 105c and one or more drugs supplied in a fixed amount from other infusion pumps (eg, 105a and 105b) are mixed together at merging structure 120. In some implementations, the merging structure 120 is a manifold having one main inlet 121 for receiving a carrier fluid flow and a plurality of auxiliary inlets 122 for receiving a drug flow. The shape, size, and number of inlets of the merging structure 120 can depend on the number of infusion pumps 105 used in the system. The merging structure 120 shown in FIG. 1A contains two closed auxiliary inlets for receiving a certain amount of drug supplied from the infusion pumps 105a and 105b and a carrier fluid supplied from the infusion pump 105c. And one main inlet 121 for the purpose. However, for a greater number of infusion pumps, the merging structure 120 can have additional main inlets 121 and / or auxiliary inlets 122 as needed. In some implementations, the merging structure 120 may include only one type of inlet, rather than a main inlet and an auxiliary inlet. In some implementations, the merging structure can incorporate a flow / pressure sensor that measures and compares the actual fluid flow. Such a merging structure can provide additional data that can be used to confirm that the actual and intended flow rates are in agreement.

  In some implementations, the system 100 includes an interface module 110 that serves as an interface between the computing device 115 and the plurality of infusion pumps 105. The interface module 110 can feature a first set of ports in communication with the computing device 115 and a second set of ports in communication with the infusion pump 105. The ports for communicating with computing device 115 and infusion pump 105 can be substantially different. In such cases, interface module 110 can serve as a bridge between computing device 115 and infusion pump 105. For example, if the infusion pump 105a is configured to accept input only through a serial port while the computing device 115 features only a USB port as an output port, the interface module 110 may be used to compute the infusion pump 105a. Communication with the device 115 may be provided. In this case, the interface module 110 can include a USB input port that accepts communication from the computing device 115 and a serial output port that communicates with the infusion pump 105a. In such a case, interface module 110 also includes circuitry configured to forward communications received at the USB input port to the serial output port.

  In some implementations, multiple infusion pumps 105 in system 100 can have different input ports. In such cases, interface module 110 may feature various output ports configured to communicate with different infusion pumps 105. In general, the input and / or output ports of the interface module 110 are, for example, serial ports, parallel ports, USB ports, IEEE 1394 interfaces, Ethernet ports, wireless transmitters, wireless receivers, Bluetooth®. Modules, PS / 2 ports, RS-232 ports, or any other port configured to support connection of interface module 110 with computing device 115 and / or infusion pump 105 may be included. Interface module 110 may also include additional circuitry to facilitate communication between different types of input and output ports.

  The interface module 110 can be implemented using any combination of software and / or hardware modules. Interface module 110 may be implemented as a stand-alone unit or may be incorporated into another device, such as computing device 115 or infusion pump 105, for example. In some cases, the interface module 110 may include a processing device that allows additional functionality on the interface module 110 to be implemented. For example, interface module 110 can be configured to monitor infusion pump 105 (eg, in conjunction with various sensors) and provide computing device 115 with appropriate feedback on the performance of infusion pump 105. In such a case, the processing device on the interface module 110 can determine whether certain feedback information should be sent back to the computing device 115. In some implementations, the interface module 110 can also facilitate communication between the infusion pumps 105. In some implementations, the interface module 110 may also uniquely identify each infusion pump and corresponding data.

  The computing device 115 can include, for example, a wireless device such as a laptop, desktop computer, or smartphone, a tablet device such as a personal digital assistant (PDA), an iPhone, and an ipad. . The computing device 115 can be configured to execute an algorithm that determines the amount of fluid to be delivered from the infusion pump 105. In some implementations, the algorithm is implemented via software that can include a set of computer-readable instructions tangibly embodied on a computer-readable storage device. In some implementations, the computer readable storage device may be a non-transitory computer readable medium such as, for example, a hard disk, a compact disk, or a memory device. In some implementations, the computing device 115 may determine the amount of fluid to be delivered from the infusion pump 105 based on a mathematical model that characterizes fluid flow along the fluid path 123 in some implementations. It is configurable. For example, based on a mathematical model of fluid flow along the fluid path 123, the computing device 115 may determine the amount of fluid to be delivered from the infusion pump 105 so that a specific drug delivery profile is achieved at the delivery point 125. The amount may be determined. The computing device 115 communicates a defined amount to the infusion pump 105 directly or via the interface module 110. The computing device 115 can be configured to communicate with the interface module 110 and / or the infusion pump 105 via a wired connection, a wireless network, or any combination thereof.

  In some implementations, the system 100 includes at least one display. The display can be part of one or more computing devices 115, interface module 110, or infusion pump 105. In other implementations, the display can be a stand-alone unit coupled to one or more of infusion pump 105 or interface module 110. The display can be configured to present users with a console that not only displays numerical parameters, drug types, and system details, but also presents a real-time graphical display of the predicted drug delivery profile based on the parameters entered by the user It is. Based on these parameters, the associated software is configured to calculate and graphically display the intended drug delivery profile (the value selected by the user) and the predicted drug delivery time course as defined by the model, for example. Is possible. Where relevant, safety boundaries above and below the drug delivery rate can be overlaid on the graph, and important inflection points and time intervals can also be shown. The graphical display can be updated in real time to reflect changes in parameters such as carrier fluid flow rate and drug flow rate. In some implementations, the display can include an electronic ink screen, a liquid crystal display (LCD), or a light emitting diode (LED) screen. Wireless portable devices such as iPhone® or Eyepad® can also be used as a display.

  In some implementations, the computing device 115 can be configured to monitor flow profiles in various parts of the system 100. One or more sensors can be deployed at various locations to detect such a flow profile. For example, the sensor may detect the actual amount of drug delivered by the infusion pump 105a and provide information to the computing device 115 via a feedback loop. Similarly, a sensor that detects the amount of carrier fluid supplied by the infusion pump 105c by a fixed amount can be provided. In some implementations, one or more sensors can detect various parameters of the mixed flow in the fluid path 123. Such parameters can include, for example, the flow rate or speed at a particular point, the amount of a particular drug in the mixture, the amount of carrier fluid in the mixture, and the like. Data from the sensor can be analyzed by computing device 115 (or possibly interface module 110) and presented graphically on a display.

  In some implementations, a visual and / or audible alarm can be triggered if a certain parameter of the drug delivery profile is detected to be outside the normal or safe range. For example, an audible and / or visual alarm can be triggered when it is determined that the amount of drug expected to be delivered at a future time (eg, by a predictive model) is outside an acceptable range. In some implementations, based on detecting when at least one of current drug flow rate, current carrier fluid rate, or predicted drug delivery profile is outside a corresponding predefined range. Alarm can be triggered. The corresponding predefined range is pre-stored (eg, in a database for storing drug libraries or drug-related parameters) and made available to a computing device that determines whether an alarm should be triggered. obtain. The graphical display can also be configured to visually reflect these alarms (eg, using a blinking value or color change). The software can be configured to trigger alarms or warnings based not only on unexpected or unsafe values at the current moment, but also on those values that are expected to occur in the future if the current settings are maintained It is. In addition, the software can be configured to monitor for malfunctions via feedback from the pump, such as an unplanned outage of carrier flow, and to provide a warning accordingly. Whether the alarm should be triggered can be determined by the computing device 115, the interface module 110, or the infusion pump 105. Such alarms and a drug library of acceptable drug parameters against which a specific drug profile should be compared are described in further detail in US Pat. No. 5,681,285, the entire contents of which are here Incorporated by reference.

  The fluid path 123 facilitates the propagation of fluid supplied from the infusion pump 105 (and mixed together at the confluence structure 120) to the target 130. In general, the fluid path 123 terminates at a delivery point 125. If the target 130 is a human patient or animal, the delivery point 125 can be, for example, intravenous, intraosseous, subcutaneous, arterial, intrathecal, or epidural delivery of fluid propagated through the fluid pathway 123. Can be made easier.

  The fluid path 123 can include one or more components. In some implementations, the merging structure 120 (eg, a manifold) can be considered part of the fluid path 123. The fluid path 123 can also include, for example, one or more of a tube (eg, an intravenous tube), a catheter (eg, a vascular access catheter), a needle, a stopcock, and a fitting. In some implementations, the components of the fluid path 123 can be represented using one or more corresponding structural parameters. Structural parameters can include, for example, the number of inlets in the manifold, the length, diameter, or volume of the catheter, the number of bends in the fluid path, and the volume of the fluid path 123. In some implementations, the fluid path 123 can also include at least a portion of the fluid path between the infusion pump 105 and the merging structure 120. In some implementations, the volume of the fluid path 123 is referred to as “dead volume”. In some implementations, the term “dead space” is used as an equivalent term for “dead volume”.

  FIG. 1B shows a schematic block diagram of another example of a system 150 for controlling fluid delivery. The system 150 includes a plurality of fluid sources 152a, 152b, and 152c (generally 152) that deliver fluid (eg, drug and carrier fluid) to the target 130. Fluid from the plurality of sources 152 is mixed with each other at the confluence structure 120, conveyed along the fluid path 123, and delivered to the target 130 at the delivery point 125. One or more of the fluid sources 152 can be containers (such as intravenous (IV) fluid containers) from which fluid includes, but is not limited to, gravity or pressurization (given internally or externally). Flow to the confluence structure 120 by an additional method of fluid delivery. One or more of the fluid sources 152 may be an infusion pump, such as the infusion pump 105 described above with reference to FIG. 1A. In some implementations, a combination of containers and infusion pumps can be used as multiple fluid sources 152. For example, medication can be delivered from a container while carrier fluid is delivered from an infusion pump.

  System 150 further includes a controllable valve 155 between source 152 and merging structure 120. In some implementations, a controllable valve 155 can be placed between each source 152 and the merging structure 120. Alternatively, at least one of the sources 152 can be directly connected to the merging structure without the controllable valve 155 being interposed. In some implementations, if controllable valve 155 is placed between source 152 and merging structure 120, system 150 may also include constant pressure valve 160 between corresponding source 152 and controllable valve 155. it can. Thus, the constant pressure valve 160 is located “upstream” from the controllable valve 155.

  The constant pressure valve can be configured to maintain a constant upstream pressure for the fluid flowing through the controllable valve 155. In some implementations, the source 152 can also maintain a constant upstream pressure. For example, if the source 152 is a controlled infusion pump, the infusion pump can be configured to maintain a constant upstream pressure. In some cases, constant pressure can be maintained by gravity flow, intravenous pump flow, or other mechanisms. In some implementations, an intravenous pump can be used to provide a pressure differential that exceeds the rated capacity of linear pressure regulators 160.

  The controllable valve 155 can be configured to provide a controllable resistance to the flow entering the merging structure 120. For example, controllable valve 155 can be configured to restrict flow according to a desired setting under a constant upstream pressure. The desired setting can be deduced from the principles of hydrodynamics, for example by applying the following equation:

Q = (K · P · r ⁴ ) / (n · l) (1)
Where Q represents the flow, K is a constant, P represents the difference between the upstream and downstream pressures, r is the radius of the tube connecting the constant pressure valve and the controllable valve, and n is Represents the viscosity of the fluid, l is the length of the tube.

  Since the tube length is fixed, for a fluid of substantially constant viscosity, the flow is proportional to the fourth power of the radius. Thus, the flow can be controlled if the controllable valve 155 can be used to control the radius (or cross-sectional area) of the tube. Various types of controllable valves 155 can be used in the methods and systems described herein. In some implementations, the controllable valve 155 is a pinch valve that can be configured to change the cross-sectional area of the tube in which the valve is disposed. For example, the controllable valve 155 can include a gripper or clamp that can apply a force to the tube to change the cross-sectional area of the tube. In some implementations, a substantially continuous management of the inner diameter or cross-sectional area of the tubing 157 can provide precise delivery of a specified fluid volume. In some cases, the resistance to flow can be proportional to the energy supplied to valve 155. The energy supplied can be electrical energy, air energy, or another form.

  In some implementations, the controllable valve 155 can include one or more actuators that can be electrically controlled to change the force applied by the valve on the tube. The one or more actuators can include, for example, a shape memory alloy that changes shape based on the magnitude of the current through the alloy. The amount of force applied by the controllable valve 155 can be controlled, for example, by changing the current through the shape memory alloy.

  An example of a shape memory alloy is Ni-Ti, that is, a nickel titanium alloy. Other suitable shape memory alloys such as copper-zinc-aluminum-nickel or copper-aluminum-nickel can also be used. Shape memory alloys typically undergo a thermoelastic phase transformation from a martensite phase at a temperature below the phase transition temperature of the material to an austenite phase when heated through the phase transition temperature. Below the phase transition temperature, the alloy is plastically deformed and remains deformed until heated through the phase transition temperature, the point at which it returns to its original shape. The resistivity characteristics of the shape memory alloy material can be used to heat it to a temperature above the corresponding phase transition temperature. For example, when current flows through an element made of a shape memory alloy, the element can be heated to a temperature above the phase transition temperature. This can then change the shape of the element. The shape memory alloy element can be disposed in the controllable valve 155 such that the element provides a variable force against the gripping or clamping of the valve 155 in various deformed states.

  In some implementations, one or more of the control valves 155 can be controlled by electrical control signals from the interface module 110. The control signal can be based on the desired amount of flow through the corresponding controllable valve 155 and can be determined using the predictive model described herein. In some implementations, the flow rate from the source is not controlled by the interface module, but instead the flow is controlled by controlling the controllable valve 155 under a constant pressure that can be ensured by the constant pressure valve 160. Be controlled. In some implementations, the interface module 110 can be used to control one or more sources 152 and one or more controllable valves 155. For example, the drug flow can be controlled via controllable valve 155 while the carrier fluid is controlled by controlling the output of the source. In some implementations, the control signal from the interface module can be converted to a different form (eg, mechanical or pneumatic) to drive the actuator.

  Since the pipe 157 in which the controllable valve is disposed is typically made of a flexible material (eg silicone), the force applied to the pipe 157 changes the cross section of the pipe, thereby passing through the cross-sectional area. Can affect the amount of fluid that can flow. However, other materials or structures that allow the flow rate through the tube to be changed by the controllable valve 155 are within the scope of this disclosure.

  Using equation (1), the relationship between flow Q and inner radius r (and consequently cross-sectional area) for any given change in pressure P, pipe length l, and fluid viscosity n. Can be calculated. FIG. 1C shows the relationship between tube inner radius and flow Q assuming a constant pressure drop, a constant pipe length, and a constant fluid viscosity. The example in FIG. 1C shows that the radius of the tube decreases at a non-linear rate as it is reduced to about 10% (0.1X) of the original radius (1X). Since the amount of power consumed to control the controllable valve is typically less than the amount of power consumed to control the source 152, low power such as a portable and / or battery operated drug delivery system For application examples, a controllable valve strategy can be used. Other settings in which the system 150 can be used include, for example, a lifesaving unit including those specializing in the treatment of critically ill pediatric patients, an operating room for delivery of intravenous anesthesia, an interventional procedure room including a cardiac catheter room including.

  Now referring to FIG. 2, an example of a dead volume is illustrated through a manifold 205 which is an example of a merging structure. Manifold 205 includes four auxiliary inlets 222 and one main inlet 221. The auxiliary inlet 222 facilitates connection with the tube 225 exiting from the drug infusion pump. The main inlet 221 facilitates connection with the tube 230 exiting from the carrier infusion pump. In some implementations, the drug infusion pump and the carrier infusion pump can be substantially similar to the infusion pump 105 described with reference to FIG. 1A. Tube 235 is connected to outlet 232 of manifold 205. Tube 235 connects manifold 205 to catheter 240. In some implementations, the catheter 240 can include various sizes of introducers or sheaths, such as a 9Fr introducer, an 8Fr sheath, or an 8.5Fr sheath. In some implementations, the catheter can include any standard single or multi-port central venous catheter and pulmonary artery catheter (including adult size catheters or pediatric patient size catheters). In some implementations, the catheter can be a peripheral venous catheter or an intraarterial, intraosseous, intrathecal, epidural, subcutaneous, or other catheter, or cannula device. In this example, the dead volume is the volume between the star 210 and the star 220. The asterisk 210 represents the point where the drug first enters the carrier fluid, and the asterisk 220 represents the point where the mixture of drug and carrier fluid enters the target (eg, the patient's bloodstream). In this example, the star 220 also represents the delivery point 125 described with reference to FIG. 1A.

  In general, the dead volume constitutes a space that the mixture of drug and carrier fluid must traverse before reaching the target 130. In some implementations, the carrier fluid can be used to accelerate propagation across the dead volume. However, in some cases, including those implementations where drug and / or carrier flow is slow, dead volume can cause a significant delay for a certain amount of drug delivered by the infusion pump when reaching target 130 There is sex. In some implementations, the dead volume serves as a reservoir for drugs that are inadvertently delivered when the flow is changed. In some implementations, discrepancies between the intended delivery profile (based on medication delivered in a fixed volume by the corresponding infusion pump 105) and the actual delivery profile at the delivery point 125 may be, for example, flow prediction This can be avoided by algorithmic control of the flow in the fluid path 123 based on the model. Such algorithms include, for example, dead volume, parameters of confluence structure 120 (eg, manifold), fluid path 123 components (eg, intravenous and intravascular catheters), drug and carrier fluid flow rate changes, and the like Factors including the relationship between such flow rates can be taken into account. In some implementations, appropriate algorithmic control of the flow in the fluid pathway reduces (or at least deterministically) delays in delivering the intended dose of drug to the target 130 at a desired time. ).

Modeling mixed flows Modeling mixed flows (ie, a mixture of one or more drugs and a carrier fluid) allows for algorithmic control over the time course of drug delivery (delivery profile), thereby making the use of drug infusion systems more It can be safer and more predictable. In some implementations, a mixed flow model can be used to provide guidance, monitoring, visualization, and control of drug injection.

  In some implementations, model-based visualization can increase the safety of drug infusion by providing a graphical display of future drug delivery profiles. For example, a model-based graphical display can show the clinician the predicted results of his decision on medication, carrier flow, and vascular access catheter and manifold selection. In some implementations, the model can also be used for training purposes. For example, the model can be used as the basis of an educational software package or simulator for training clinicians (nurses, physicians, pharmacists) about the actual behavior of the drug infusion system.

  In some implementations, modeling the mixed flow includes characterizing the flow using differential equations derived from physical principles. Since the model considers and explains various parameters, the model is also referred to as an integrated model. The integrated model can be, for example, radial diffusion (molecules moving towards the tubing or catheter wall), axial diffusion (molecules moving along the flow axis), laminar flow (smooth bulk fluid flow), and Several factors are considered, including the physicochemical properties of the drug and the interaction between these and other factors.

  In some implementations, only the drug flow (or drug concentration along the fluid path over time) can be modeled to control the drug delivery profile. Various predictive models can be used to model drug flow, drug concentration, and / or mixed fluid flow. An example model will now be described in connection with mixed flow modeling. The model described can be easily extended to model other flows such as drug flow or carrier fluid flow. It should also be noted that the following model is described for illustrative purposes and should not be considered limiting. Other predictive models characterizing drug concentration, drug flow, carrier flow, or mixed flow along the fluid path over time fall within the scope of the disclosure.

  In some implementations, the mixed flow is modeled using a Taylor dispersion formula that includes parameters for radial diffusion, axial diffusion, and laminar flow. Taylor dispersion typically deals with longitudinal dispersion in the flow tube, but can be extended for any type of flow where velocity gradients exist. In some implementations, the Taylor dispersion used to model the mixed flow can be expressed as:

  Where D represents the molecular diffusion coefficient, u represents the axial velocity of the fluid through the tube, x represents the axial distance along the tube, t represents time, R represents the radius of the tube, c represents the concentration of the substance (eg, a dye or drug). The short bars above the parameters u and c represent intermediate or average values. The average concentration of the substance is calculated over the cross section of the tube. The flow is generally assumed to be non-turbulent and can be represented using a low Reynolds number. The Reynolds number is a dimensionless number that gives a measure of the ratio of inertial force to viscous force and quantifies the relative importance of these two types of force for a given flow condition.

In some implementations, equation (2) can be implemented numerically using a forward difference model. Under experimental setup, the model represented by equation (2) can be verified by tracking the dye as it flows through the fluid path via quantitative spectroscopy. The parameters in the model can be defined in various ways. For example, the molecular diffusion coefficient D (whose unit can be cm ² / sec) can be retrieved or calculated based on known measurements, or experimentally estimated based on the molecular nature of the drug Can do. In such cases, the value of D can vary from drug to drug. In some implementations, the intermediate axial velocity of the fluid can be calculated from the sum of the flow rates and the nature of the fluid path 123. In some implementations, the equations for the model are solved for the concentration of substance (drug, carrier fluid, etc.) averaged over the cross section of the fluid path 123. The equation can be solved over the length of the fluid path for a given time.

  In some implementations, the model uses the empirical dead volume of the fluid path 123 rather than the measured dead volume. An empirical dead volume is, for example, a change in diameter between a stopcock, manifold, tube, etc., and a change in angle in the fluid path 123 (eg, a stopcock port can be encountered at right angles to the manifold). The irregularity of the fluid path 123 including will be described. The empirical dead volume can be determined experimentally, for example, by examining a series of empirical dead volume candidates and selecting the one that best fits the experimental control curve in the least-squares sense. In some implementations, other model parameters may also be determined experimentally. By using empirically defined parameters, the need for complex computationally intensive modeling based on precise physical characteristics of the infusion setup that can vary between clinical situations can be avoided. Similarly, other parameters (eg, parameters related to fluid propagation through the fluid path 123) can be estimated or calibrated empirically using appropriate control curves.

  In some implementations, parameters including empirical dead volumes, infusion sets, and drug pumps, manifolds, tubing, their individual configurations such as catheters (including individual lumens of multi-lumen catheters), connectors, stopcocks, etc. It can be stored in an electronic library that contains information about the elements. This infusion system component library can be used in conjunction with the system described in this document. The physical parameters that can be stored in such a library include the dead volume of each individual element and structural information such as the inner diameter, length, and configuration of the fluid path. Such configuration information can include multiple right-angle bends (or other flow angle changes) in the fluid path and changes in the diameter of the fluid path. The stored information may be specific to each physical element used within the fluid delivery passage. The electronic library can be integrated with the system described in this document for use in any of the visualization, prediction, and control modes. In some implementations, details of each fluid path physical element available to clinicians in the organization are loaded into the organization-specific component library.

  In some implementations, catheters and other infusion system elements are identified via bar codes, RFID, or similar tagging techniques to facilitate easy automated or semi-automated identification of catheters or other infusion system elements. Can be easily. Alternatively or in conjunction with such an identification method, elements can be selected from the infusion system component library, for example via a scrollable menu or pull-down menu provided as part of the user interface.

  In some implementations, by solving the integrated model equation, the distal tip of the intravascular catheter (eg, FIG. 2) from the point at which drug is added to the carrier flow (eg, point 210 of FIG. 2) at any given time. The concentration of the drug along the fluid path 123 to the second point 220) is obtained and predicts how the concentration will be along the fluid path 123. Knowing the concentration of the drug at various parts of the fluid path 123 can be useful in predicting the time course of drug delivery to the target 130. Such time course knowledge can be used to create a control algorithm that achieves precise control of medication. In some implementations, the equations can be solved using approximation methods such as forward difference numerical approximation. The forward difference numerical approximation can include dividing the fluid path 123 (in some implementations, can include manifolds, intravenous tubes, and catheters) into a number of small separate segments. In such cases, a solution for the concentration of drug in each segment may be calculated for each incremental time step, thereby obtaining an accurate estimate of drug delivery over time (eg, at delivery point 125). it can. In some implementations, other numerical approximation algorithms can be used to solve the equations, including other definite difference methods such as backward difference or central difference numerical approximation.

  In some implementations, rapid control of ongoing changes in drug delivery can be achieved by the relationship of flow rate and drug concentration to drug delivery, the relationship of drug concentration in the mixed fluid to the ratio of drug flow to carrier flow, Based on physical principles including one or more of rapid communication of flow changes based on fluid incompressibility and limited compliance of elements of the infusion system fluid path. In some cases, drug delivery (mass / time) can be considered substantially equal to flow rate (volume / time) × drug concentration (mass / volume). The concentration of the drug in the mixed fluid is the ratio of the drug fluid flow divided by the total (mixed) fluid flow multiplied by the concentration of the original drug in the (unmixed) drug flow (ratio is a dimensionless number). Substantially equal. In some implementations, changes in drug flow and carrier flow can be made in parallel, and the ratio of drug flow to mixed fluid flow can be kept constant. In some implementations, this type of control facilitates maintaining a constant drug concentration in the mixed fluid and making precise changes in drug delivery as described further in the next section. In some implementations, maintaining a constant concentration of the mixed drug can be performed in conjunction with an algorithm based on the prediction model or other algorithms that are not directly dependent on the prediction model.

  In some implementations, algorithms based on maintaining a constant concentration of mixed drugs (as described above) are used in conjunction with algorithms built on predictive models to speed up drug delivery. And total fluid delivery can be minimized while still allowing precise changes.

Applications The methods and systems described herein can be used in a variety of ways to achieve useful results. For example, predictive models such as the models described above and other principles described above, including maintaining a constant concentration of mixed drugs, can be used for drug delivery processes in a drug delivery system (eg, system 100 described with reference to FIG. 1A). Can be applied at various stages. Some such application examples are described below as examples.

Reducing Drug Delivery Onset Delay In some cases, drug delivery onset delay can be reduced by controlling the drug infusion pump using an algorithm based on a model of the flow in the fluid path. Such onset delay can appear in the difference between activation of the drug infusion pump and the time when the appropriate amount of drug actually reaches a goal, such as the patient's blood flow. Such differences can be important for rapid drug administration, and can have high clinical significance and consequences, especially in critical care settings where carrier and drug infusion flow rates are typically low. Reducing the difference by simply increasing the flow rate of the carrier fluid can have undesirable consequences. For example, high levels of carrier fluid flow (if maintained) can sometimes result in excessive volume delivery to the patient. On the other hand, reducing the flow of carrier fluid can also reduce drug delivery.

  In some implementations, the proportions of carrier fluid and drug flow can be kept uniform (ie, at a constant ratio) to achieve a fixed concentration of drug along the fluid path 123. The tuned control of the carrier fluid infusion pump in conjunction with the medication infusion pump (eg, infusion pumps 105a and 105b in FIG. 1A) is quick and responsive by maintaining the ratio between the medication in the fluid path 123 and the carrier fluid. Some control can be given.

  In some implementations, the decrease in drug delivery onset delay is determined by first setting a fast carrier and drug flow, eg empirically divided by one time constant (time constant defined as dead volume, or total flow rate). This can be achieved by maintaining these flows for a given period of time (such as dead volume) and then immediately reducing the carrier and drug flow to steady state levels. In some implementations, this may be done by first setting the carrier flow to the maximum allowable rate so that the drug concentration would be when the carrier and drug flow were reduced to a steady state level. It relates to setting the fluid flow of the drug to a rate that achieves the concentration of the drug in equal fluid paths. Carrier and drug flow are first maintained at a high level for one time constant and then lowered to a target level. As described above, maintaining the ratio between the carrier flow and the drug flow keeps the drug concentration constant. In such implementations, there may be a short undershoot of drug delivery as the flow is reduced, but the target drug delivery rate is achieved relatively fast. This also provides a means of limiting fluid volume delivery to the patient.

  FIG. 3A shows a flowchart 300 illustrating an example of a sequence of operations for reducing drug delivery onset delay. The sequence of operations shown in flowchart 300 can be performed, for example, in a system substantially similar to system 100 described with reference to FIG. 1A.

  Acting may include receiving 310 system information at the processing unit. The system information can include information and parameters regarding a drug infusion system substantially similar to the system 100 described with reference to FIG. 1A. In some implementations, the system information includes parameters related to one or more of merging structures (eg, manifolds), drug infusion pumps, intravascular catheters, intravascular piping, and the like. For example, system information includes information about the cross-sectional diameter of the endovascular tube, the maximum output rate of the infusion pump, the length of the intravascular catheter, the number of manifold inlets, the position of the stopcock in the tube, and the material of the tube Can be included. System information can be used to define the parameters of the formula used in modeling the flow in the fluid path.

  In some implementations, system information is entered manually by a user (eg, a clinician) via an input device coupled to a computing device (eg, computing device 115). In some implementations, the computing device can be configured to access a database that stores system information (eg, organized as a library) for various systems. For example, relevant information for infusion pump 105 can be stored in a database as a library linked to a particular type of infusion pump. Similarly, information about other components of the system, such as manifolds, tubes, catheters, etc. can also be stored in the database. In some implementations, the database can store information about the physical or chemical properties of individual infused drugs. The database can also be configured to store, for example, a visual and / or numerical history of pump input parameters and a calculated drug delivery profile.

  The computing device can be configured to access the database to retrieve information about the component device upon detecting and / or identifying the presence of the component device in the system. In some implementations, the computing device identifies component devices based on manual user input. In some implementations, the computing device may also automatically identify the component device when, for example, reading a component device identification tag (eg, a radio frequency identification (RFID) tag or barcode). It is configurable. In such cases, the computing device may communicate with a tag reader (eg, an RFID reader or barcode reader) to identify the component device. The tag reader can identify the component device and provide the computing device with associated parameters (eg, structural parameters) associated with the component device. In some cases, parameters associated with component devices can be retrieved from a database. In some, such identification may be facilitated by near field communication (NFC) technology.

The operation also includes receiving 320 dosage information at the computing device. Dosage information can be retrieved manually by a computing device from a user (eg, a clinician) or automatically retrieved from a database. The dosage information includes, for example, the target amount of drug to be delivered to the target, the time of drug delivery, the carrier flow rate Q _c , the drug flow rate Q _d , the total flow rate Q _T , the drug delivery rate dd, the target drug delivery rate dd. _target, steady state rate ss, can include maximum allowable carrier flow Q _cmax, the target steady-state carrier flow Q _css, various parameters such as the storage agent concentration c _d. Some of these parameters can be calculated from other parameters. For example, the total flow rate can be calculated as the sum of the drug flow rate Q _d and the carrier fluid flow rate Q _c . In some implementations, the dosage information can also include information about a safe range associated with a given drug. Such information can be used to trigger an alarm for overdose.

The operation may also include determining 330 flow parameters. The flow parameters include, for example, steady state drug flow rate Q _dss , steady state total flow rate Q _Tss , steady state mixed flow concentration c _ss , steady state carrier flow rate and steady state drug flow rate. A proportionality constant between and the like. In some implementations, the initial flow parameter is defined as a combination of received and calculated values. For example, the initial carrier flow level can be set to the maximum level Q _cmax and the mixed drug (in the most proximal upstream portion of the mixed fluid) equal to the desired steady state drug concentration. Can be set to a rate that achieves a concentration of.

In some implementations, determining the flow parameters may include determining 333 a steady state concentration c _ss of the mixed stream (ie, the mixture of drug and carrier fluid). The steady state concentration of the mixed flow can be calculated from the values of Q _dss and Q _Tss , for example. Such a calculation can be expressed using the following equation:

Q _dss = dd _target / c _d (3)
Q _Tss = Q _css + Q _dss (4)
c _ss = (Q _{dss /} Q _Tss ) * c _d (5)
Determining the flow parameter can also include determining a proportionality constant p (335). In some implementations, the proportionality constant represents the ratio between steady state carrier flow and steady state drug flow, and is given by:

p = Q _css / Q _dss (6)
The operation may also include initiating (340) the flow of medication and carrier fluid according to the defined flow parameters and the received system and dosage information. In some implementations, the carrier fluid flow is initiated at the maximum allowable rate so that:

Q _c = Q _cmax (7)
In some implementations, drug flow can be initiated such that a proportionality constant is maintained for maximum allowable carrier flow. In such a case, the drug flow is given by:

Q _d = Q _cmax / p (8)
The operation further includes monitoring (350) the concentration of the drug along the fluid path over time, eg, using a forward difference model, based on the Taylor dispersion equation (Equation 2). This can include solving for the concentration of drug as a function of axial distance x along the fluid path and time t. Therefore, the concentration of the drug can be expressed as c (x, t). In some implementations, the drug delivery rate dd at the delivery point is monitored. Expressing the effective length of a tube or fluid pathway as L, the amount of drug delivered can be expressed as:

dd = c (L, t) * Q _T (9)
The operation further includes periodically checking (360) whether the drug delivery rate at the delivery point substantially matches the target drug delivery rate dd _target . In some implementations, the time interval can be expressed as dt. If the drug delivery rate does not match the target delivery rate, the monitor is repeated after another time interval dt.

If the drug delivery rate dd at the delivery point substantially matches the _target drug delivery rate dd _target , the operation can include adjusting 370 the drug flow and the carrier flow. In some implementations, one or more of Q _c and Q _d are reduced in a controlled manner. For example, Q _c and / or Q _d may still be at a high initial value shortly after dd reaches the target drug delivery rate ddtarget. In such a case, Q _c and Q _d may need to be reduced while maintaining the ratio of drug flow to carrier fluid flow represented by the _target drug delivery rate dd _target and p. In such an implementation, Q _c and Q _d are adjusted by controlling the respective infusion pump.

In some implementations, Q _c and / or Q _d are adjusted based on predicting the concentration of drug that reaches the delivery point after a particular time. This can be done using a model of the flow in the fluid path. For example, using the current velocity of the mixed fluid (eg, derived from the configuration of Q _T and possibly the fluid path), the delivery point will be reached after time dt if the current Q _T is maintained. Position x ₁ can be found. This position can be determined as follows, for example.

x ₁ = L−u (t _current ) dt (10)
Where L is the length of the fluid path used in the model and u (t _current ) is the current velocity of the mixed fluid. In the above case, the expected drug concentration after time dt is therefore given by c (x ₁ , t _current ) calculated using the model. In some implementations, the calculated drug concentration can be used to calculate a new flow rate that will maintain the target drug delivery rate dd _target at the delivery point. For example, a new flow rate can be calculated as follows.

Q _Tnew = dd _target / c (x ₁ , t _current ) (11)
Q _dnew = Q _Tnew / (1 + p) (12)
Q _cnew = Q _Tnew −Q _dnew (13)
_Where Q _Tnew , Q _dnew , and Q _cnew represent the new total flow rate, the new drug flow rate, and the new carrier fluid flow rate, respectively. The existing carrier fluid flow and existing drug flow can then be replaced with the new calculated flow as follows.

Q _c = Q _cnew (14)
Q _d = Q _dnew (15)
The operation can also include checking 380 whether the drug concentration at the delivery point substantially matches the steady state concentration c _ss . This can be expressed as:

c (L, t) = c _ss ? (16)
In some implementations, the check can be performed periodically after the time interval dt. If the steady state concentration has not been reached, the operation can include re-adjusting the flow of the drug and carrier fluid (370). If a steady state concentration is reached, the operation can include maintaining 390 the drug and carrier fluid flow at the last calculated level. In such a case, the following condition is satisfied for all x along the fluid path:

dd = dd _target (17)
c (x, t) = c _ss (18)
In the exemplary use case of the above sequence of operations, the clinician can first select a target carrier flow and a maximum acceptable carrier flow and a target drug delivery rate. The clinician's selection is then received at the computing device that controls the infusion pump. The characteristics of the infusion system (manifold, intravascular catheter, and any intravascular tubing that may be used) are also input, detected, or received so that dead volume or empirical dead volume can be considered in the calculation. . First, the carrier flow is kept at the maximum possible level, and the drug flow is the same as the final drug concentration would be if the carrier and drug flow were reduced to a steady state level, The level is set to achieve drug flow along the upstream portion of the fluid pathway. When the infusion pump is activated, the drug is quickly swept through the fluid path toward the patient and traverses the dead volume of the infusion system. As the drug moves along the fluid path, a model is used to track the progress. FIG. 3B shows an exemplary schematic graph of drug concentration along a fluid path (referred to as “distance along the fluid path” in the figure) at a given moment. Point 395 represents the place where the drug and carrier fluid come together, and point 396 represents the place where the mixed flow enters the patient's bloodstream. Curve 392 shows the leading edge diffusion of the drug, which is why it has a wave appearance rather than a step function.

  Continuing with the example, the model tracks the flow and concentration of drug (drug delivery) reaching the patient (ie, reaching the point where the vascular access catheter terminates in the blood stream). The drug delivery rate (mass / time) can be expressed as fluid flow rate (volume / time) x drug concentration (mass / volume). Referring again to FIG. 3B, when the leading edge of the wavefront reaches the patient, drug delivery increases at a point 393 until the target drug delivery is reached. In this regard, model calculations are used in the form of “intelligent feedback” or “adaptive” control to anticipate the concentration of drug that will reach the patient after one slight time increment if the flow remains unchanged be able to. Based on this finding of potential upcoming drug delivery, the carrier and drug flow can be adjusted to maintain drug delivery at the target rate. The ratio between carrier flow and drug flow is maintained so that the concentration of drug along the remainder of the fluid pathway remains at the same fixed level. At each time increment, drug flow and carrier flow are adjusted downward to maintain a fixed drug concentration along the remainder of the fluid path until a flat drug concentration hits the patient's bloodstream. In that regard, both carrier flow and drug flow are at a desired steady state rate, and drug delivery is also at a steady state target.

  Changes to the carrier flow and drug flow are made with an infusion pump, but these changes in flow are transmitted almost instantaneously to the “patient end” of the fluid path due to the incompressibility of the fluid.

  In some implementations, the algorithm as described also provides a means to limit fluid volume delivery to the patient in order to control the rapid onset of drug delivery. This may be most important for patients who may not tolerate excessive volumes due to organ system dysfunction. Compared to conventional means of initiating drug initiation (which introduces the drug at the desired flow rate while leaving the carrier fluid flow unchanged), a rapid onset algorithm such as those described herein requires minimal Delivers additional total fluid.

  An example of an algorithm feedback loop is shown schematically in FIG. 3C. In this illustration, input (I) 397 is the drug and carrier flow as set, for example, with an infusion pump. Factors such as diffusion and dead volume between the pump and the patient can affect the time course of the drug reaching the patient (O) 398. With feedback collected using the model described above, an appropriate adjustment 399 can be made to input 397 as shown in the feedback loop of FIG. 3C.

Controlling the change in drug delivery profile In some cases, the infusion pump can be adjusted to change the drug delivery profile to be delivered to the target (eg, change the dose). In some cases, the discrepancy between the timing of changes to the pump settings and the actual time at which the target drug dose reaches the target (eg, patient blood flow) can be significant. The methods and systems described herein can also be used to achieve precise control of drug delivery profile changes.

  In some implementations, an ongoing change (eg, increase or decrease) in the drug delivery profile can be achieved almost instantaneously via adjustment of the total flow (drug plus carrier). Such adjustment can be based on maintaining a ratio between the carrier flow and the drug flow, and thus a fixed concentration of the drug along the fluid path. For example, to double drug delivery, the total flow can be doubled by doubling each of the carrier flow and drug flow. Typically, the incompressibility of the fluid causes such changes in flow to be immediately reflected at the target end of the fluid path. In some implementations, the drug concentration is kept constant along the fluid path, so the target drug delivery profile (mass / time) is used while using the model to calculate the appropriate drug flow and carrier flow. ) Changes to total flow (volume / time) changes.

  FIG. 4 shows a flowchart 400 illustrating an exemplary sequence of operations for controlling a drug delivery profile. The sequence of operations shown in flowchart 400 may be performed, for example, in a system substantially similar to system 100 described with reference to FIG. 1A.

  Acting may include receiving 410 system information at the processing device. The received system information may be substantially similar to the system information described above with reference to operation 310 of FIG. 3A. System information may be received manually or via automatic input. For example, system information can be manually entered by a user (eg, a clinician) via an input device coupled to a computing device (eg, computing device 115). Alternatively, system information may be retrieved (eg, from a database) or automatically identified (eg, by reading an RFID tag or bar code) of a component device.

The operation also includes receiving dosage information (420). In some implementations, dosage information can include initial carrier fluid flow and drug flow (represented as Q _c0 and Q _d0 respectively). In some cases, the initial flow may be a steady state flow. Dosage information can be received from a user (eg, a clinician) or retrieved automatically. For example, the initial flow value may be received from an infusion pump or from one or more sensors that monitor the flow rate delivered by the pump. The dosage information can also include a desired change in the target drug delivery profile dd _target at one or more future times. The desired change may be received in advance or on a real-time basis (ie, at a substantially close time when the change is desired). In some implementations, there may be multiple target drug delivery profiles corresponding to different future times. The initial target drug delivery profile can be represented as dd _target0, and the subsequent target drug delivery profiles can be represented as dd _target1 , dd _target2, etc.

  The operation also includes determining (430) initial parameters for drug flow and carrier fluid flow. For example, determining the initial parameters can include calculating an initial drug concentration and a proportional factor p between the carrier flow and the drug flow. In some implementations, the initial state is a steady state. That is, the drug and carrier fluid were pre-flowing long enough to achieve some steady state drug delivery. Determining the initial parameters can also include, for example, calculating an initial drug delivery profile that can be calculated as follows.

dd _target0 = Q _d0 * c _d (19)
In some implementations, the initial parameters can also include a total initial flow rate, which can be calculated as the sum of the drug and carrier fluid flow rates as follows:

Q _T0 = Q _c0 + Q _d0 (20)
The concentration of the mixed medicine in the initial state can also be calculated as follows, for example.

c _ss = (Q _d0 / Q _T0 ) * c _d (21)
For example, the ratio can be calculated as follows.

p = Q _c0 / Q _d0 (22)
The operation also includes receiving a new target delivery profile (440). The new target delivery profile can be retrieved from a pre-loaded list (eg, given dosage information by the user) or received on a real-time basis. In some implementations, the new target delivery profile can be retrieved from a pre-loaded list at a preset time.

The operation further includes determining (450) a new flow rate to meet the new target delivery profile. The new flow rate can then be used by the computing device to adjust the infusion pump at a specific time corresponding to the delivery profile change. For example, it is possible that the delivery profile dd _target1 to be valid at a particular time t _1, to adjust the infusion pump with a new flow rate corresponding to the delivery profile dd _target1. In some implementations, the new flow rate is defined before a specific point in time. In some implementations, calculating the new flow rate is based on maintaining the steady state drug concentration c _ss by keeping the proportionality factor p unchanged. In some implementations, the new total flow rate Q _T1 can be calculated as follows.

Q _T1 = dd _target1 / c _ss (23)
For example, the flow of a new medicine can be calculated as follows.

Q _d1 = Q _T1 / (1 + p) (24)
The new carrier flow can be calculated, for example, as the difference between the new total flow and the new drug flow as follows:

Q _c1 = Q _T1 −Q _d1 (25)
The existing flow rate can then be replaced with the calculated new flow rate so that the new delivery profile becomes effective at a particular point in time. The operation also includes maintaining a new flow rate (460) until the next delivery profile occurs (eg, T2). In some implementations, operation 440 is repeated at _T2 for the corresponding drug delivery profile dd _target2 and possibly the new total flow Q _T2 . In some implementations, the mixed drug concentration c _ss and the proportional factor p are _unchanged for the new drug delivery profile dd _target1 .

Maintaining Steady State In some implementations, after a target drug delivery profile has been achieved, there may be a period during which drug flow and carrier flow are maintained at a particular level, during which time substantial Change is not expected. In some implementations, the methods and systems described herein can be used to minimize the amount of carrier fluid delivered to the target. This can be done, for example, by slowly reducing the carrier fluid flow rate to a specified target flow rate during the maintenance phase. In order to keep drug delivery within a specific range substantially near the target delivery rate, the rate of carrier fluid flow reduction can be selected based on the model. The specific range can be chosen, for example, by a clinician. In some implementations, as the carrier fluid flow rate is gradually adjusted downward, the drug concentration slowly increases along the fluid path. In such cases, target carrier fluid flow can be achieved over a period of time, which allows for optimization of total fluid delivery. The model can be used to track the calculated concentration of drug along the fluid pathway. In some cases, if a change in drug delivery is required at any point during the maintenance phase (either while gradually reducing the carrier fluid rate or after the target carrier flow is achieved) Such modifications can be made as described in to achieve a new desired target drug delivery profile.

Drug Stop Phase In general, stopping drug delivery can be achieved in substantially the same manner as reducing drug delivery. In some implementations, the ratio p between carrier flow and drug flow is gradually changed during the drug stop phase. This typically maintains a small carrier flow during the stop phase, for example, to maintain venous access to the patient and deliver drugs in the dead volume at a negligible rate of delivery to the patient. be able to. In some implementations, the model allows calculation of the residual concentration of drug along the fluid pathway during this “washout” period. If for any reason the carrier and / or drug flow is strengthened during this time, such a calculation accounts for the remaining drug along the fluid path and ensures that no unwanted bolus of drug is delivered to the target. To.

Controlling multiple drugs and carriers Even though the above application examples are generally described with reference to only one drug flow and one carrier fluid flow, more A large number of flows can be controlled. In some implementations, a single carrier fluid stream can be used to deliver multiple agents through the same fluid pathway. In some implementations, an appropriate data repository, such as, for example, a multiple drug electronic library, can provide guidance on which drugs can be safely delivered together through the same fluid pathway. A data repository, such as a multi-drug electronic library, can be accessed by a computing device that controls the infusion pump to achieve a secure delivery profile. If non-conforming drugs are attempted to be delivered together (eg, drugs that may react with each other to generate harmful substances, or drugs that may reduce each other's efficacy), the computing device may Based on the information from, it can be configured to trigger an alarm or otherwise stall the attempted delivery.

  In addition to identifying these types of drug-drug interactions, in some implementations, when two or more drugs are delivered over a fluid pathway with a single carrier fluid, each drug has clinical parameters. A “criticality” based may be assigned. Criticality ranking is, in some implementations, the half-life and potency of a drug (eg, the degree of ability to change the hemodynamic parameters of a given dose of drug acting on blood vessels) and other Among the factors can be related to biological targets. An acceptable variation for each drug is assigned to control the delivery of a given drug while maintaining the level of delivery of other drugs injected through the same line within a safe and therapeutically desirable range. Can give ability. Acceptable variability and “criticality” rankings for individual drugs may be incorporated into a new extension of the multiple drug library (data repository referred to above) in some implementations.

  When multiple drugs are delivered together, for example to the same patient, in some implementations, the drugs can be mixed together in appropriate amounts and delivered in a fixed volume from a single drug infusion pump. In some implementations, each of the plurality of drugs can be dispensed from a separate drug infusion pump and mixed together in a merging structure such as a manifold. In such a case, each of the plurality of drug infusion pumps and the carrier fluid infusion pump can be controlled in a synchronized manner as described above. For example, a model can be used to calculate the concentration of each of the drugs along the fluid path at any moment. The model can also be used to calculate the delivery profile of each drug at the delivery point. For each drug, all of the other drug flows combined with the carrier flow can be treated as a single combined carrier flow, and the model can be applied to predict the delivery profile of each drug it can. In some implementations, these predictions can also serve as a basis for visualization as described for the single drug plus carrier case of this document.

  In order to improve the control of the delivery of multiple medications from multiple medication infusion pumps via a single fluid path (as described above), some implementations depend on criticality and acceptable variation. Thus, each drug can be assigned to an appropriate port on a confluence structure such as a manifold. This allocation process may utilize parameters such as dead volume or empirical dead volume taken from an electronic library of catheter or infusion set parameters. For example, a highly critical drug may be assigned to a manifold port with the lowest available port dead volume (which may be recommended to be administered through).

  In some implementations, various algorithms can be used to ensure delivery optimization for each individual drug and for the combined drugs. In addition to assigning a drug to a manifold port based on criticality, acceptable variation, and catheter / infusion set parameters, the algorithm, in some implementations, can tolerate changes to other drugs. Can be designed to maintain each drug within a certain variation. For multiple drugs delivered through a single fluid pathway, in some cases, if changes are made to a subset of those drugs, all drugs can be maintained at a deterministic desired level. It may not be possible. In these cases, some implementations may involve conditional optimization, in which case less critical drugs are still within safe and effective range, while tighter tolerances for more critical drugs. For the purpose of maintenance, some deviation within acceptable variations is allowed for each drug.

  As an example of such control, consider the case where four medications are delivered via four port manifolds. The four drugs are combined with the carrier fluid and transmitted as a mixed fluid through a single fluid path. Suppose that it is desired to double the dose of the most critical drug (eg, drug 1) at a given time. Using the algorithm described above, the flow of drug 1 can be doubled and the carrier flow can be increased to maintain the concentration of drug 1 in the fluid pathway. If the flow of drug 2, drug 3, and drug 4 is kept constant, a temporary increase in the delivery of drugs 2, 3, and 4 can be calculated using the techniques described above. This is because the mass of those drugs already in the fluid pathway are moved more quickly into the patient (due to faster flow). If the peak level of those less critical drugs stays within their acceptable variation, this provides a solution to changing the delivery of the most critical drugs quickly and accurately. The flow may be further adjusted after the initial change to minimize over-volume delivery using the algorithm described above.

  To extend this example, if the second most critical drug (referred to as Drug 2) would move out of its acceptable range using the above method of changing the dosage of Drug 1, Change the flow of drug 2 (and / or drug 3, drug 4, and carrier fluid) to allow drug 2 to still reach the target level quickly, but drug 2 remains within acceptable levels can do. This falls into the area of conditional optimization mentioned above. In some implementations, Drug 1 can also be allowed to vary within the specified tolerances to allow this type of optimization.

  As a second example of multiple drug control, consider the case where a rapid start (rapid onset) of all four drugs (for the four drug plus carrier configuration described above) is desired. In such cases, the rapid start algorithm described above for a single drug plus carrier is also applied. Each of the four drug flows and carrier flows is first set to a high level, first the carrier flow is set to the maximum allowable rate, and each drug fluid flow is steady at the carrier and drug flows. Set to a rate that achieves a drug concentration in the fluid path that would be the same as the drug concentration would be when reduced to a state level. After models such as those described above have determined that the most critical drug has reached the target drug delivery rate, changes in drug flow and carrier flow (for each of the four simultaneously delivered drugs) in parallel In practice, the ratio of drug flow to mixed fluid flow can be kept constant for each of the drugs.

  The methods and examples described herein have manifolds with different dead volumes between access points (eg, linear manifolds) and access ports that are aligned in different access points (eg, radial or parallel orientation). Equally valid for manifolds that have little or no dead volume difference.

  In some implementations, the methods and systems described herein allow a user to make changes introduced by the simultaneous use of multiple pumps. For example, multiple infusion pumps can be integrated as part of the overall system, and their synchronized control allows, for example, more precise control of the administration of multiple drugs at the therapeutic transition point.

Examples of Use In some implementations, the methods and systems described herein can be used in an “assisted” mode where the software uses the model to provide guidance to achieve the target drug delivery profile. In such cases, the clinician may manually manipulate the infusion pump parameters. Alternatively, in the “control” mode, the software can be configured to make recommended changes to pump settings for clinician approval. In some implementations, the system may operate in a “visualization” mode in which the system is used to primarily display predicted drug delivery based on values selected by the clinician. In this mode, the clinician operates the infusion pump and the system monitors what the pump is doing. However, even in the “visualization” mode, being able to see visual and audible alerts and a graphical display of expected drug delivery can facilitate making informed decisions. Providing user guidance in the form of warnings, recommendations, or direct changes to pump settings can be important when involved in tuning multiple pumps as part of the overall clinical management using the system.

  For decision support and educational purposes, the system may also operate in “predictive” mode. In this predictive mode, the clinician or learner can enter different selections of infusion tubing, manifolds, or vascular access catheters into the software along with the pump settings. They can then look at the resulting drug delivery profile predictions and explore various hypothetical scenarios without actually administering the medication. This takes advantage of the capabilities of the system as an educational tool.

  In some implementations, at least a portion of the system can be integrated into an integrated chip and thus can be integrated with other electronic devices such as infusion pumps. The system's ability to run on laptops, tablet PCs, and other portable devices improves mobility, thereby enabling the use of the system in a variety of clinical situations including, for example, lifesaving emergency in emergency situations. Can be extended. Mobility is also the safe management of infusion therapy when, for example, a patient moves from an intensive care unit (ICU) to an operating room (OR) or radiation room, or from an emergency room (ER) to an ICU, OR, etc. Can be easily.

  In some implementations, at least a portion of the pump control system can be embedded, such as in the microprocessor control mechanism of the infusion pump itself. Such an infusion pump can act as a stand-alone unit for delivering medication without being integrated with the output of other pumps.

  In some implementations, the methods and systems described herein can be used in the delivery of total intravenous anesthesia (TIVA) for patients in need of surgery. Traditional anesthetic delivery systems required the ability to deliver a certain amount of inhalation anesthesia (eg, nitrous oxide, sevoflurane, etc.). However, the development of short-acting intravenous agents with analgesic (eg, remifentanil), sedation / hypnosis (eg, propofol), and muscle relaxant (eg, cisatracurium) can all be anesthetized by intravenous infusion. Is possible. In some implementations, the methods and systems described herein can be configured for field use such as military or trauma / rescue situations and remote location situations such as space medicine. While transporting interface modules, processing equipment (eg rugged laptops or tablet PCs), and a small number of infusion pumps, syringes, and tubing in small containers of limited weight and size (eg backpacks) The delivery of anesthetic combinations can be controlled by intravenous infusion in various environments.

  In some implementations, the methods and systems described herein allow for precise control of drug and fluid delivery in settings where fluid volume must be limited for clinical reasons. For example, an infant or small child undergoing surgery or treatment with an ICU or OR may not tolerate a large volume of fluid. Severely ill adult patients or adult patients with advanced disease (eg, renal failure) may not be able to tolerate the large volumes of fluids administered during the course of treatment with infusion medications. In such cases, a precisely controlled (time and dose) infusion of sedation, analgesia, anesthesia, heart, or vasoactive medication may be delivered using the methods and systems described herein.

Overview of Computing Device FIG. 5 is a schematic diagram of a computer system 500. System 500 can be used for operations described in connection with any of the computer-implemented methods described herein according to one implementation. System 500 can be incorporated into various computing devices such as desktop computer 501, server 502, and / or laptop computer 503. System 500 includes a processor 510, a memory 520, a storage device 530, and an input / output device 540. Each of components 510, 520, 530, and 540 are interconnected using system bus 550. The processor 510 can process instructions for execution within the system 500. In one implementation, the processor 510 is a single thread processor. In another implementation, processor 510 is a multithreaded processor. The processor 510 may process instructions stored in the memory 520 or on the storage device 530 to display graphical information for a user interface on the input / output device 540.

  Memory 520 stores information in system 500. In some implementations, memory 520 is a computer-readable medium. The memory 520 can include volatile memory and / or non-volatile memory.

  Storage device 530 may provide mass storage for system 500. In one implementation, the storage device 530 is a computer readable medium. In various different implementations, the storage device 530 may be a floppy disk device, a hard disk device, an optical disk device, or a tape device.

  Input / output device 540 provides input / output operations for system 500. In some implementations, the input / output device 540 includes a keyboard and / or pointing device. In some implementations, the input / output device 540 includes a display unit for displaying a graphical user interface. In some implementations, the input / output device can be configured to accept verbal (eg, spoken) input. For example, the clinician can provide input by speaking into the input device.

  The described features can be implemented in digital electronic circuitry or in computer hardware, firmware, or combinations thereof. The features can be implemented in a computer program product tangibly embodied in an information carrier in a machine readable storage for execution by a programmable processor, for example, the features operate on input data and output Can be performed by a programmable processor that executes a program of instructions that perform the functions of the described implementation. The described features include at least one programmable processor coupled to receive data and instructions from and transmit data and instructions to a data storage system, at least one input device, and at least one output device. It can be implemented in one or more computer programs that can be executed on a programmable system. A computer program includes a set of instructions that can be used directly or indirectly in a computer to perform an activity or produce a result. A computer program can be written in any form of programming language, including a compiled or interpreted language, which contains modules, components, subroutines, or other units suitable for use as a stand-alone program or in a computing environment. It can be deployed in any form including.

  Suitable processors for execution of a program of instructions include, by way of example, both general and special purpose microprocessors, and one of a single processor or multiple processors of any kind of computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The computer includes a processor for executing instructions and one or more memories for storing instructions and data. Generally, a computer also includes or is operatively coupled to communicate with one or more mass storage devices for storing data files. Such devices include magnetic disks such as internal hard disks and removable disks, magneto-optical disks, and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include, for example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices, magnetic disks such as internal hard disks and removable disks, and magneto-optical disks. And all forms of non-volatile memory including CD-ROM and DVD-ROM discs. The processor and memory can be supplemented with or incorporated into an ASIC (Application Specific Integrated Circuit).

  To provide interaction with the user, the features are a display device such as a CRT (cathode tube) or LCD (liquid crystal display) monitor for displaying information to the user, and a mouse or track that allows the user to provide input to the computer. It can be realized on a computer having a keyboard such as a ball and a pointing device.

  The computer system includes a back-end component such as a data server, or includes a middleware component such as an application server or Internet server, or includes a front-end component such as a client computer having a graphical user interface or Internet browser, Or it can be realized by any combination thereof. The components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, for example, LANs, WANs, and computers and networks that form the Internet.

  The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a network, such as the one described. The relationship between a client and a server is generated by a computer program that runs on each computer and has a client-server relationship with each other.

  The processor 510 executes instructions related to the computer program. The processor 510 may include hardware such as logic gates, adders, multipliers, and counters. The processor 510 may further include separate arithmetic logic units (ALUs) that perform arithmetic and logical operations.

  The methods and systems described herein are further illustrated with the following results, but are not intended to limit the scope of the claimed invention.

Example 1 Reduction of Drug Delivery Onset Delay FIG. 6A shows an exemplary set of plots illustrating the reduction of drug delivery onset delay by using the methods and systems described herein. The plot represents the drug concentration (in mg / ml) at the delivery point as a function of time. In this experiment, the drug infusion pump was switched on with a 6 minute sign. Methylene blue was used as a drug. An adult catheter (9Fr introducer) was used for these experiments. The confluence structure was a linear stopcock manifold where the drug entered the fluid pathway at position 3. Plot 610 (referred to as “conventional”) represents the case where no algorithm was used to control the drug flow and carrier flow held constant at 3 ml / hr and 10 ml / hr, respectively. Plot 620 (referred to as “algorithm”) represents the case where the above-described model is used to control the drug and carrier fluid pump using the measured dead volume. Plot 630 (referred to as “algorithm experience Vd”) represents the use of the model described above to control the drug and carrier fluid pump using empirical dead volume. The expected steady state rate of drug delivery was 0.005 mg / ml or 0.005 mg / min. As can be seen from plot 610, the steady state start time is about 50 minutes without the algorithm control described herein. However, using the model in conjunction with measured dead volume (as seen from plot 620) or empirical dead volume (as seen from plot 630), the delay was significantly reduced.

  FIG. 6B shows another set of exemplary plots illustrating the reduction in drug delivery onset delay by using the methods and systems described herein. In this case, the catheter used was a 16g lumen of the triple lumen central venous line. All other parameters were substantially the same as the corresponding parameters of the experiment described in FIG. 6A. Plot 640 (referred to as “conventional”) represents the case where no algorithm was used to control drug and carrier flow. Plot 650 (referred to as “algorithm experience Vd”) represents the case where the above model is used to control the drug and carrier fluid pump using empirical dead volume. Comparing plots 640 and 650, it can be seen that controlling carrier and drug flow using the methods and systems described herein significantly reduces delay.

  FIG. 6C shows another set of exemplary plots illustrating the reduction in drug delivery onset delay by using the methods and systems described herein. In this case, a 4Fr pediatric central venous line catheter was used. The merging structure was a stopcock coupling manifold, where the drug entered the fluid path at position 1. The drug used was methylene blue and the corresponding infusion pump was switched on with a 6 minute sign. Plot 660 (referred to as “naive”) shows an example where no algorithm was used to control drug and carrier flow held constant at 0.5 ml / hr and 1.5 ml / hr, respectively. Represents. Plot 670 (referred to as “algorithm”) represents the case where the above model is used to control the drug and carrier fluid pump using the measured dead volume. Plot 680 (referred to as “predicted delivery”) represents the expected steady state rate of drug delivery, fixed at 0.00085 mg / ml. Comparing plots 660 and 670, it can be seen that controlling the carrier and drug flow using the methods and systems described herein significantly reduces the onset delay.

Example 2 Control of Drug Delivery Profile FIG. 7 shows an exemplary set of plots illustrating improved control of drug delivery profile achieved using the methods and systems described herein. The plot represents the concentration of drug (in mg / ml) at the delivery point as a function of time for adult subjects. In this experiment, an abrupt step change was made from steady state (represented as a “predicted steady state” 730 plot) with and without algorithmic control of the infusion pump. The ideal or intended step change is represented by dashed line 735. As shown by the dashed line 735, the drug pump setting was approximately half of the steady state value at approximately time 740 and was approximately double the steady state value at approximately time 750. The drug infusion pump was switched on with a 6 minute sign. Methylene blue was used as a drug. The catheter used was a 16g lumen with a triple lumen central venous line. The confluence structure was a stopcock connection manifold and the drug entered the fluid path at position 3. Plot 720 (referred to as “conventional”) represents the case where no algorithm was used to control drug and carrier flow held constant at 3 ml / hr and 10 ml / hr, respectively. Plot 710 (referred to as “algorithm”) represents the use of the model described above to control the drug and carrier fluid pump using the measured dead volume. The expected steady state rate of drug delivery (plot 730) was 0.005 mg / ml or 0.005 mg / min. Comparing plots 710 and 720, it can be seen that abrupt changes can be better controlled using the methods and systems described herein.

Other Embodiments While the invention has been described in connection with the detailed description thereof, the foregoing description is intended to illustrate rather than limit the scope of the invention as defined by the appended claims. Should be understood. For example, the methods and systems described herein can be used to control pumps other than infusion pumps. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims (39)

A system for predicting a drug delivery profile, comprising:
At least one drug pump for generating a flow of drug, said at least one drug pump supplying at least a first volume of a first drug, and at least one carrier fluid pump for generating a flow of carrier fluid;
A merging structure configured to receive a flow of the drug and a flow of the carrier fluid to generate a mixed flow;
A fluid path for carrying the mixed stream between the confluence structure and a delivery point;
A processor configured to predict the drug delivery profile at the delivery point based on determining an expected temporal change in drug concentration at the delivery point using at least a model of the mixed flow; And the model includes a plurality of parameters relating to the propagation of the mixed flow through the fluid path.   The system of claim 1, further comprising a control module configured to control the flow of the drug and the flow of the carrier fluid such that a specific drug delivery profile is achieved at a future time.   The control module is further configured to calculate a rate of the drug flow and a rate of the carrier fluid flow at a given time such that the specific drug delivery profile is achieved at the future time. The system according to claim 2.   4. The system of any one of claims 1-3, further comprising a display device for displaying data based on the predicted drug delivery profile.   a corresponding predefined desired or safe range in which at least one of i) current drug flow rate, ii) current carrier fluid rate, and iii) predicted drug delivery profile is associated with the drug. 4. The system of any one of claims 1-3, further comprising at least one alarm configured to be triggered upon detection of being outside.   The system of claim 5, wherein the safe range associated with the medication is retrieved from a database.   4. The system of any one of claims 1-3, further comprising at least one sensor configured to provide data about the flow rate of the mixed stream in a particular portion of a delivery path.   The control module controls the drug flow and the carrier fluid flow such that a ratio of the drug and the carrier fluid in the mixed flow over a given portion of the fluid path is substantially fixed. The system of claim 2, configured as follows.   9. The processor of claims 1-3 and 8, wherein the processor is further configured to predict the drug delivery profile at the delivery point based on user input parameters for the drug flow and the carrier flow. The system according to any one of the above.   The parameters related to the propagation of the mixed flow through the fluid path are i) radial diffusion, ii) axial diffusion, iii) laminar flow through the fluid path, and iv) physical or chemical properties of the drug. 9. A system according to any one of claims 1-3 and 8, comprising parameters characterizing one or more of them.   9. The model according to any one of claims 1-3 and 8, wherein the model includes structural parameters representing at least one characteristic of the drug pump, the carrier fluid pump, the confluence structure, or the fluid pathway. system.   The system of claim 11, wherein the structural parameter includes a dead volume associated with the fluid path.   13. The system of claim 12, wherein the dead volume is determined empirically by examining a series of empirical dead volume candidates and selecting the one that best fits the control curve in the least squares sense.   The system of claim 11, wherein the processing device is further configured to access a storage device that stores the structural parameter.   9. The process of any of claims 1-3 and 8, wherein the processing device is configured to identify at least one of the drug pump, the carrier fluid pump, the merging structure, and the fluid pathway based on an identifier. The system according to claim 1.   The system of claim 15, wherein the identifier is a radio frequency identification (RFID) tag or barcode, and the processing device is coupled to an RFID tag reader or barcode reader.   And further comprising at least one additional drug pump for delivering a fixed amount of at least a second drug, wherein the control module is configured to achieve a specific delivery profile of the second drug at the future time point. The system of claim 2, configured to control the flow of the two drugs.   The system according to any one of claims 1-3, 8, and 17, wherein at least one of the drug pump and the carrier fluid pump is a syringe pump or an infusion pump.   The system of claim 17, further comprising a display device for displaying data about predicted drug delivery profiles of the first and second drugs. A method for predicting the delivery rate of a drug at a delivery point, comprising:
Receiving at a processing device one or more operating parameters related to a drug pump supplying a fixed amount of drug and a carrier fluid pump supplying a fixed amount of carrier fluid;
Delivery of the drug at the delivery point by the processing device by predicting a time variation of the concentration of the drug at the delivery point based at least on a mathematical model of a mixed flow through a fluid path terminating at the delivery point Providing a rate,
The mixed flow comprises the drug and the carrier fluid, and the model includes a plurality of flow parameters related to the one or more operating parameters and the mathematical model of the mixed flow. A system for controlling a drug delivery profile comprising:
At least one drug pump for generating a flow of drug, said at least one drug pump supplying at least a first volume of a first drug, and at least one carrier fluid pump for generating a flow of carrier fluid;
A merging structure configured to receive a flow of the drug and a flow of the carrier fluid to generate a mixed flow;
A fluid path for carrying the mixed stream between the confluence structure and a delivery point;
By controlling the drug flow rate and the carrier fluid flow rate so that the ratio between the drug flow rate and the carrier fluid flow rate is substantially fixed over a range of time, the at the delivery point A control module configured to control a drug delivery profile, wherein the mixed stream is varied to achieve a specific drug delivery profile.   Further comprising at least one controllable valve disposed upstream from the merging structure, wherein the control module controls the drug delivery profile at the delivery point by controlling flow through the controllable valve; The system of claim 21.   A constant pressure valve disposed upstream from the controllable valve, the constant pressure valve configured to maintain a constant pressure upstream of the controllable valve for fluid flowing through the controllable valve; The system of claim 22.   24. The control module is further configured to adjust a drug delivery rate at the delivery point within the time period by simultaneously controlling the flow rate of the drug and the flow rate of the carrier fluid. The system according to any one of the above.   24. The system of any one of claims 21-23, wherein the concentration of drug in the drug stream is substantially fixed over the range of time.   24. The system of any one of claims 21-23, wherein the control module adjusts the drug delivery rate to achieve at least a predicted drug delivery rate calculated using the mixed flow model.   24. The control module is further configured to adjust the drug delivery profile such that over-volume delivery over time while maintaining target drug delivery within tolerance is substantially reduced. The system according to any one of the above.   27. The system of claim 26, wherein the model includes a plurality of parameters relating to propagation of the mixed flow through the fluid path. The control module is
At the beginning of the time range, set the initial drug flow rate and the initial carrier fluid flow rate to a substantially high value within a corresponding tolerance range, and the drug at the delivery point after a predetermined amount of time has elapsed 24. The system of any one of claims 21-23, further configured to reduce the flow rate of the drug and the flow rate of the carrier fluid such that a delivery profile is achieved.   The predetermined amount of time is required for the mixed flow to traverse the fluid path when the drug flow rate and the carrier fluid flow rate are set to the initial drug flow rate and the initial carrier fluid flow rate, respectively. 30. The system of claim 29, substantially equal to time. A method for controlling a drug delivery profile comprising:
Receiving at a processing device information about the flow rate of the drug for a drug pump that supplies a fixed amount of drug and information about the flow rate of the carrier fluid for a carrier fluid pump that supplies a fixed amount of carrier fluid;
The delivery by adjusting the drug flow rate and the carrier fluid flow rate by a control module such that the ratio between the drug flow rate and the carrier fluid flow rate is substantially fixed over a range of time. Controlling the drug delivery profile in terms of points.   32. The method of claim 31, further comprising varying a flow rate of a mixed stream comprising the drug and the carrier fluid to achieve a specific drug delivery profile. When executed, the processor
Based on at least a mathematical model of a mixed flow through a fluid path that is subject to one or more operating parameters relating to a drug pump that supplies a fixed amount of drug and a carrier fluid pump that supplies a fixed amount of carrier fluid and terminates at the delivery point A computer readable storage device having instructions encoded thereon for causing a rate of delivery of the drug at the delivery point to be determined by predicting a change in the concentration of the drug at the delivery point over time,
The mixed flow comprises the drug and the carrier fluid, and the model includes a plurality of flow parameters related to the one or more operating parameters and the mathematical model of the mixed flow. When executed, the processor
Receiving information about the flow rate of the drug related to the drug pump supplying a fixed amount of drug and information about the flow rate of the carrier fluid related to the carrier fluid pump supplying a fixed amount of carrier fluid; and A command to control the drug delivery profile at the delivery point by controlling the flow rate of the drug and the flow rate of the carrier fluid such that the ratio between is substantially fixed over a range of time A computer readable storage device encoded in A method for predicting a delivery rate at a delivery point, comprising:
Receiving at least one operating parameter associated with a first container supplying a fixed amount of medication and a second container supplying a fixed amount of carrier fluid in a processing device, wherein at least one of the drug and the carrier fluid One is supplied at a pre-determined pressure and is further timed by the processor to the concentration of the drug at the delivery point based at least on a mathematical model of the mixed flow through the fluid path terminating at the delivery point. Determining a delivery rate of the drug at the delivery point by predicting a change;
The mixed flow includes the drug and the carrier fluid, and the model includes a plurality of flow parameters related to the one or more operating parameters and the mathematical model of the mixed flow.   36. The method of claim 35, wherein the predefined pressure is controlled by a linear pressure control valve.   36. The method of claim 35, wherein the predefined pressure is controlled with a substantially constant force.   38. The method of claim 37, wherein the substantially constant force is provided by gravity. A system for controlling a drug delivery profile comprising:
A first controllable valve for controlling drug flow;
A second controllable valve for controlling the flow of the carrier fluid;
A merging structure configured to receive a flow of the drug and a flow of the carrier fluid to generate a mixed flow;
A fluid path for carrying the mixed stream between the confluence structure and a delivery point;
By controlling the drug flow rate and the carrier fluid flow rate so that the ratio between the drug flow rate and the carrier fluid flow rate is substantially fixed over a range of time, the at the delivery point A control module configured to control a drug delivery profile, wherein the mixed stream is varied to achieve a specific drug delivery profile.